Sutskever and LeCun: Scaling LLMs Won't Yield More Useful Results

Summary

When two of the most influential people in AI both say that today’s large language models are hitting their limits, it’s worth paying attention.In a recent long-form interview, Ilya Sutskever – co-founder of OpenAI and now head of Safe Superintelligence Inc. – argued that the industry is moving from an “age of scaling” to an “age of research”. At the same time, Yann LeCun, VP & Chief AI Scientist at Meta, has been loudly insisting that LLMs are not the future of AI at all and that we need a completely different path based on “world models” and architectures like JEPA.As developers and founders, we’re building products right in the middle of that shift.This article breaks down Sutskever’s and LeCun’s viewpoints and what they mean for people actually shipping software.1. Sutskever’s Timeline: From Research → Scaling → Research AgainSutskever divides the last decade of AI into three phases:1.1. 2012–2020: The first age of researchThis is the era of “try everything”:convolutional nets for visionsequence models and attentionearly reinforcement learning breakthroughslots of small experiments, new architectures, and weird ideasThere were big models, but compute and data were still limited. The progress came from new concepts, not massive clusters.1.2. 2020–2025: The age of scalingThen scaling laws changed everything.The recipe became:More data + more compute + bigger models = better results.You didn’t have to be extremely creative to justify a multi-billion-dollar GPU bill. You could point to a curve: as you scale up parameters and tokens, performance climbs smoothly.This gave us:1.3. 2025 onward: Back to an age of research (but with huge computers)Now Sutskever is saying that scaling alone is no longer enough:The industry is already operating at insane scale.The internet is finite, so you can’t just keep scraping higher-quality, diverse text forever.The returns from “just make it 10× bigger” are getting smaller and more unpredictable.We’re moving into a phase where:The cl...